diff --git a/_data/people.yml b/_data/people.yml index 56355dc..ab3203e 100644 --- a/_data/people.yml +++ b/_data/people.yml @@ -38,7 +38,14 @@ phd: webpage: "https://en.uit.no/ansatte/person?p_document_id=686752&p_dimension_id=88131" postdoc: - - name: "John Doe" + - name: "Andrea Cini" + image: "/figs/people/ac.png" + bio: "Andrea is an SNSF Swiss Postdoctoral Fellow, affiliated with USI and Oxford Univeristy. His research focuses on spatio-temporal models and is the creator of Torch Spatiotemporal." + scholar: "https://scholar.google.com/citations?user=bQI2UIUAAAAJ&hl=en" + webpage: "https://andreacini.github.io/" + github: "https://github.com/andreacini" + linkedin: "https://www.linkedin.com/in/andrea-cini/" + twitter: "https://x.com/andreacini1994" collaborator: - name: "Simone Scardapane" diff --git a/_site/feed.xml b/_site/feed.xml index ec1e51c..45fb3f5 100644 --- a/_site/feed.xml +++ b/_site/feed.xml @@ -1,2 +1,2 @@ -Jekyll2024-10-20T12:58:42+02:00http://localhost:4000/feed.xmlNorthernmost GraphML GroupThe Northermost GraphML group in the world, based in Tromsø, Norway. +Jekyll2024-10-22T13:36:58+02:00http://localhost:4000/feed.xmlNorthernmost GraphML GroupThe Northermost GraphML group in the world, based in Tromsø, Norway. \ No newline at end of file diff --git a/_site/figs/people/ac.png b/_site/figs/people/ac.png new file mode 100644 index 0000000..9284df3 Binary files /dev/null and b/_site/figs/people/ac.png differ diff --git a/_site/figs/publications/koopman.gif b/_site/figs/publications/koopman.gif new file mode 100644 index 0000000..23a93dd Binary files /dev/null and b/_site/figs/publications/koopman.gif differ diff --git a/_site/people.html b/_site/people.html index bd95200..17c705a 100644 --- a/_site/people.html +++ b/_site/people.html @@ -165,17 +165,37 @@

Researchers and postdocs

- John Doe's profile picture + Andrea Cini's profile picture
-

John Doe

-

+

Andrea Cini

+

Andrea is an SNSF Swiss Postdoctoral Fellow, affiliated with USI and Oxford Univeristy. His research focuses on spatio-temporal models and is the creator of Torch Spatiotemporal.

@@ -212,7 +232,7 @@

Michele Guerra

- + diff --git a/_site/publications.html b/_site/publications.html index b03081a..8060fd8 100644 --- a/_site/publications.html +++ b/_site/publications.html @@ -69,7 +69,7 @@

Interpreting Temporal Graph Neural Networks with K
- Figure for Interpreting Temporal Graph Neural Networks with Koopman Theory + Figure for Interpreting Temporal Graph Neural Networks with Koopman Theory
@@ -219,7 +219,8 @@

Graph-based Forecasting with Missing Data through volume = {235}, series = {Proceedings of Machine Learning Research}, publisher = {PMLR} -} +} +

diff --git a/_site/theses/gnn-physics/index.html b/_site/theses/gnn-physics/index.html index 25ff5c2..8fcb7ae 100644 --- a/_site/theses/gnn-physics/index.html +++ b/_site/theses/gnn-physics/index.html @@ -19,11 +19,11 @@ - + +{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2024-10-22T13:36:58+02:00","datePublished":"2024-10-22T13:36:58+02:00","description":"Graph neural networks and Physics","headline":"Graph neural networks and Physics","mainEntityOfPage":{"@type":"WebPage","@id":"http://localhost:4000/theses/gnn-physics/"},"publisher":{"@type":"Organization","logo":{"@type":"ImageObject","url":"http://localhost:4000/figs/NGMLGlogo2.png"}},"url":"http://localhost:4000/theses/gnn-physics/"} diff --git a/_site/theses/graph-pooling/index.html b/_site/theses/graph-pooling/index.html index 25095fa..06834b9 100644 --- a/_site/theses/graph-pooling/index.html +++ b/_site/theses/graph-pooling/index.html @@ -19,11 +19,11 @@ - + +{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2024-10-22T13:36:58+02:00","datePublished":"2024-10-22T13:36:58+02:00","description":"Clustering and graph coarsening with Graph Neural Networks","headline":"Clustering and graph coarsening with Graph Neural Networks","mainEntityOfPage":{"@type":"WebPage","@id":"http://localhost:4000/theses/graph-pooling/"},"publisher":{"@type":"Organization","logo":{"@type":"ImageObject","url":"http://localhost:4000/figs/NGMLGlogo2.png"}},"url":"http://localhost:4000/theses/graph-pooling/"} diff --git a/_site/theses/polar-weather/index.html b/_site/theses/polar-weather/index.html index f62b8dc..0a28ca4 100644 --- a/_site/theses/polar-weather/index.html +++ b/_site/theses/polar-weather/index.html @@ -19,11 +19,11 @@ - + +{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2024-10-22T13:36:58+02:00","datePublished":"2024-10-22T13:36:58+02:00","description":"Polar weather prediction with Graph neural networks","headline":"Polar weather prediction with Graph neural networks","mainEntityOfPage":{"@type":"WebPage","@id":"http://localhost:4000/theses/polar-weather/"},"publisher":{"@type":"Organization","logo":{"@type":"ImageObject","url":"http://localhost:4000/figs/NGMLGlogo2.png"}},"url":"http://localhost:4000/theses/polar-weather/"} diff --git a/_site/theses/power-flow/index.html b/_site/theses/power-flow/index.html index a8c74c8..83a9389 100644 --- a/_site/theses/power-flow/index.html +++ b/_site/theses/power-flow/index.html @@ -19,11 +19,11 @@ - + +{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2024-10-22T13:36:58+02:00","datePublished":"2024-10-22T13:36:58+02:00","description":"Power flow optimization with Graph Neural Networks","headline":"Power flow optimization with Graph Neural Networks","mainEntityOfPage":{"@type":"WebPage","@id":"http://localhost:4000/theses/power-flow/"},"publisher":{"@type":"Organization","logo":{"@type":"ImageObject","url":"http://localhost:4000/figs/NGMLGlogo2.png"}},"url":"http://localhost:4000/theses/power-flow/"} diff --git a/_site/theses/text-data/index.html b/_site/theses/text-data/index.html index 2ba4e0e..2b929a6 100644 --- a/_site/theses/text-data/index.html +++ b/_site/theses/text-data/index.html @@ -19,11 +19,11 @@ - + +{"@context":"https://schema.org","@type":"BlogPosting","dateModified":"2024-10-22T13:36:58+02:00","datePublished":"2024-10-22T13:36:58+02:00","description":"📝 Description The main idea is to build graphs of documents, graphs of topics contained in them, connecting abstract concepts and ideas inside the documents. We want to detect important news, automatically classify documents and get detailed information about a topic. The approach is in the same vein as Retrieval Augmented Generation RAG but we want to leverage the graph structure for a better retrieval of information.","headline":"Graph of text data, using large language models","mainEntityOfPage":{"@type":"WebPage","@id":"http://localhost:4000/theses/text-data/"},"publisher":{"@type":"Organization","logo":{"@type":"ImageObject","url":"http://localhost:4000/figs/NGMLGlogo2.png"}},"url":"http://localhost:4000/theses/text-data/"} diff --git a/figs/people/ac.png b/figs/people/ac.png new file mode 100644 index 0000000..9284df3 Binary files /dev/null and b/figs/people/ac.png differ